Visualization, modeling and validation of chromatin interaction data

哺乳动物基因组的三维(3D)组织与基因调控密切相关，因为它可以 揭示末端调控元件与其靶基因之间的物理相互作用。最近的几个高点- 基于染色质构象捕获(3C)的吞吐量技术已经出现(如4C、5C、Hi-C 和CHIA-PET)，给了我们一个前所未有的机会来研究更高级别的基因组组织。 其中，Hi-C技术特别令人感兴趣，因为它不偏不倚地覆盖全基因组，可以 测量任意两个给定基因组座位之间的染色质相互作用强度。 然而，Hi-C资料的分析和解释仍处于早期阶段。其中一个主要挑战是如何 高效地可视化染色质相互作用数据，以便科学界将其可视化并用于 他们自己的研究。此外，由于实验程序复杂，测序成本高，Hi-C 仅在有限数量的细胞/组织类型中进行。最后，其根本机制是 染色质的相互作用在很大程度上仍然不清楚。因此，该委员会将提出以下目标： 目标1.构建一个交互式的、可定制的3D基因组浏览器。我们将建立一个互动和 可定制的3D浏览器，允许用户导航Hi-C数据和其他高通量染色质 组织数据，包括Chia-PET和Capture Hi-C。我们已经建造了3D基因组浏览器的原型 (www.3dgenome.org)。我们的浏览器将允许用户方便地浏览染色质相互作用数据 同一窗口中基因组区域的其他数据类型(如CHIP-SEQ和RNA-SEQ 同时。我们的系统还将允许用户创建他们自己的会话和查询他们自己的Hi-C 和其他表观基因组数据。目的2.利用其他基因组/表观基因组研究染色质相互作用 信息。我们将使用其他可用的基因组和表观基因组数据来预测Hi-C相互作用的频率 在相同的细胞类型中，如ChIP-Seq数据中的组蛋白修饰和转录因子。我们将建造 我们的预测模型，然后系统地归因于所有127种细胞类型的Hi-C相互作用矩阵 由于ENCODE和路线图表观基因组项目最近的努力，表观基因组是可用的。目标3. 对目标1和目标2中的计算方法进行验证实验。我们将执行20 3C 在hESC和GM细胞系中的实验，结合CRISPR/Cas9的基因组工程来评估Hi-C 目标2中的预测方法。

The three dimensional (3D) organization of mammalian genomes is tightly linked to gene regulation, as it can reveal the physical interactions between distal regulatory elements and their target genes. Several recent high- throughput technologies based on Chromatin Conformation Capture (3C) have emerged (such as 4C, 5C, Hi-C and ChIA-PET) and given us an unprecedented opportunity to study the higher-order genome organization. Among them, Hi-C technology is of particular interest due to its unbiased genome-wide coverage that can measure chromatin interaction intensities between any two given genomic loci. However, Hi-C data analysis and interpretation are still in the early stages. One of the main challenges is how to efficiently visualize chromatin interaction data, so that the scientific community to visualize and use it for their own research. In addition, due to the complex experimental procedure and high sequencing cost, Hi-C has only been performed in a limited number of cell/tissue types. Finally, the underlying mechanism of chromatin interactions remains largely unclear. Therefore, the PI will propose the following aims: Aim 1. Build an interactive and customizable 3D genome browser. We will build an interactive and customizable 3D browser, which allows users to navigate Hi-C data and other high-throughput chromatin organization data, including ChIA-PET and Capture Hi-C. We have built a prototype of the 3D genome browser (www.3dgenome.org). Our browser will allow users to conveniently browse chromatin interaction data with other data types (such as ChIP-Seq and RNA-Seq) from the genomic region in the same window simultaneously. Our system will also empower the users to create their own session and query their own Hi-C and other epigenomic data. Aim 2. Impute chromatin interaction using other genomic/epigenomic information. We will predict Hi-C interaction frequencies using other available genomic and epigenomic data in the same cell type, such as ChIP-Seq data for histone modifications and transcription factors. We will build our prediction model and then systematically impute Hi-C interaction matrices for all 127 cell types whose epigenomes are available thanks to recent effort by the ENCODE and Roadmap Epigenome projects. Aim 3. Perform validation experiments for computational method in aim 1 and 2. We will perform 20 3C experiments in hESC and GM cell lines, coupled with genome engineering by CRISPR/Cas9, to evaluate Hi-C prediction method in aim 2.